Cílem článku je nové metodické uchopení výzdoby LBK z neolitické lokality v Bylanech u Kutné Hory. Dosavadní interpretace vývoje sídliště je založena na dataci keramického materiálu a trendech vývoje nekeramických artefaktů z tzv. stavebních komplexů. Jedná se o empiricky definované chronologicko-prostorové jednotky, jejichž jádrem je dům. Výchozí otázkou je, zda se jakkoliv změní stávající model sídliště, pokud dojde k dekonstrukci stavebních komplexů. Na základě kvantitativní analýzy stylu keramické výzdoby provedené v úrovni jednotlivých archeologických objektů bylo definováno několik skupin stylu lineární výzdoby. Význam těchto skupin byl validován prostřednictvím prostorové evidence jejich výskytu. Výsledky analýzy umožňují konfrontovat stávající teoretický model neolitických sídlišť s jinou alternativou. and The aim of the article is an innovative methodological understanding of LBK pottery decoration from the site of Bylany, Central Bohemia. The existing interpretation of the settlement development is based on pottery dating and the evolution of non-ceramic artifacts from the so-called “house complexes”. These are empirically defined spatio-temporal units with the house in their centre. The initial question is whether the existing model of the settlement will change in any way if these complexes are deconstructed. Several groups of linear decoration style were defined through quantitative analysis of pottery decoration style performed at the level of individual archaeological features. The meaning of these groups was validated through analysis of their spatial occurrence. The results of the analysis allowed comparison of the existing theoretical model of Neolithic settlements with an alternative.
From 61 coking coals, 36 coal blends were prepared. Using a pilot coke oven, cokes were prepared from both 61 coking coals (Type I cokes) and 36 coal blends (Type II cokes). Coals were characterized by 14 coal characteristics and cokes by Coke Reactivity Index CRI and Coke Strength after Reaction with CO2 CSR. For the study of mutual statistic relationships among experimentally determined characteristics of coals and cokes, the Factor (FA) and Regression Analyses (RA) were used. FA distributed characteristics of coals and Type I cokes into 4 factors while characteristics of coal blends and Type II cokes were distributed into 7 factors. In case of pure coals and Type I cokes, strong relationships with high correlation coefficients (R > 0.60 ) were more abundant than in case of coal blends and Type II cokes. FA was used for the selection of coal characteristics that influence the coke quality the most significantly. These characteristics were then recalculated by RA for the predictions of CRI/CSR of Type I cokes. Predictions of CRI/CSR of Type II cokes were calculated from coal blends by the same procedure. The comparison of the predicted and experimentally determined CRI and CSR indexes showed much more reliable prediction of CRI/CSR indexes calculated from coals than calculated from coal blends. This study also explains the dominant reasons of this observation., Jana Serenčíšová, Zdeněk Klika, Ivan Kolomazník, Lucie Bartoňová and Pavel Baran., and Obsahuje bibliografii
We examine the feasibility and added value of upscaling point data of soil moisture from a small- to a mesoscale catchment for the purpose of single-event flood prediction. We test the hypothesis that in a given catchment, the present soil moisture status is a key factor governing peak discharge, flow volume and flood duration. Multiple regression analyses of rainfall, pre-event discharge, single point soil moisture profiles from representative locations and peak discharge, discharge duration, discharge volume are discussed. The soil moisture profiles are selected along a convergent slope connected to the groundwater in flood plain within the small-scale catchment Husten (2.6 km²), which is a headwater catchment of the larger Hüppcherhammer catchment (47.2 km², Germany). Results show that the number of explanatory variables in the regression models is higher in summer (up to 8 variables) than in winter (up to 3 variables) and higher in the meso-scale catchment than in the small-scale catchment (up to 2 variables). Soil moisture data from selected key locations in the small catchment improves the quality of regression models established for the meso-scale catchment. For the different target variables peak discharge, discharge duration and discharge volume the adding of the soil moisture from the flood plain and the lower slope as explanatory variable improves the quality of the regression model by 15%, 20% and 10%, respectively, especially during the summer season. In the winter season the improvement is smaller (up to 6%) and the regression models mainly include rainfall characteristics as explanatory variables. The appearance of the soil moisture variables in the stepwise regression indicates their varying importance, depending on which characteristics of the discharge are focused on. Thus, we conclude that point data for soil moisture in functional landscape elements describe the catchments’ initial conditions very well and may yield valuable information for flood prediction and warning systems.